---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: math_question_grade_detection_v12
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# math_question_grade_detection_v12

This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8913
- Accuracy: 0.7397
- Precision: 0.7255
- Recall: 0.7397
- F1: 0.7178

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- training_steps: 1500

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 0.0855 | 50   | 3.0343          | 0.1710   | 0.1287    | 0.1710 | 0.0917 |
| No log        | 0.1709 | 100  | 2.4792          | 0.3151   | 0.2979    | 0.3151 | 0.2439 |
| No log        | 0.2564 | 150  | 2.1397          | 0.4428   | 0.4101    | 0.4428 | 0.3752 |
| No log        | 0.3419 | 200  | 1.9824          | 0.4419   | 0.3872    | 0.4419 | 0.3638 |
| No log        | 0.4274 | 250  | 1.7765          | 0.5072   | 0.4772    | 0.5072 | 0.4666 |
| No log        | 0.5128 | 300  | 1.6510          | 0.5524   | 0.5347    | 0.5524 | 0.5147 |
| No log        | 0.5983 | 350  | 1.5160          | 0.5793   | 0.5501    | 0.5793 | 0.5319 |
| No log        | 0.6838 | 400  | 1.4481          | 0.5898   | 0.5608    | 0.5898 | 0.5437 |
| No log        | 0.7692 | 450  | 1.3791          | 0.6148   | 0.5758    | 0.6148 | 0.5678 |
| 1.9748        | 0.8547 | 500  | 1.3154          | 0.6196   | 0.6123    | 0.6196 | 0.5779 |
| 1.9748        | 0.9402 | 550  | 1.2399          | 0.6484   | 0.6168    | 0.6484 | 0.6119 |
| 1.9748        | 1.0256 | 600  | 1.1968          | 0.6340   | 0.6181    | 0.6340 | 0.5889 |
| 1.9748        | 1.1111 | 650  | 1.2477          | 0.6215   | 0.6014    | 0.6215 | 0.5825 |
| 1.9748        | 1.1966 | 700  | 1.2098          | 0.6340   | 0.6285    | 0.6340 | 0.5884 |
| 1.9748        | 1.2821 | 750  | 1.1316          | 0.6619   | 0.6442    | 0.6619 | 0.6385 |
| 1.9748        | 1.3675 | 800  | 1.0783          | 0.6744   | 0.6644    | 0.6744 | 0.6462 |
| 1.9748        | 1.4530 | 850  | 1.0512          | 0.6907   | 0.6728    | 0.6907 | 0.6583 |
| 1.9748        | 1.5385 | 900  | 1.0388          | 0.6945   | 0.6909    | 0.6945 | 0.6697 |
| 1.9748        | 1.6239 | 950  | 0.9954          | 0.6974   | 0.6748    | 0.6974 | 0.6707 |
| 1.0265        | 1.7094 | 1000 | 0.9812          | 0.7128   | 0.6888    | 0.7128 | 0.6874 |
| 1.0265        | 1.7949 | 1050 | 0.9717          | 0.7099   | 0.6907    | 0.7099 | 0.6852 |
| 1.0265        | 1.8803 | 1100 | 0.9437          | 0.7099   | 0.6823    | 0.7099 | 0.6866 |
| 1.0265        | 1.9658 | 1150 | 0.9724          | 0.7061   | 0.7096    | 0.7061 | 0.6800 |
| 1.0265        | 2.0513 | 1200 | 0.9168          | 0.7224   | 0.7099    | 0.7224 | 0.6976 |
| 1.0265        | 2.1368 | 1250 | 0.9097          | 0.7243   | 0.7109    | 0.7243 | 0.6996 |
| 1.0265        | 2.2222 | 1300 | 0.9072          | 0.7329   | 0.7336    | 0.7329 | 0.7083 |
| 1.0265        | 2.3077 | 1350 | 0.9028          | 0.7262   | 0.7114    | 0.7262 | 0.7033 |
| 1.0265        | 2.3932 | 1400 | 0.8951          | 0.7301   | 0.7145    | 0.7301 | 0.7068 |
| 1.0265        | 2.4786 | 1450 | 0.8949          | 0.7378   | 0.7339    | 0.7378 | 0.7154 |
| 0.687         | 2.5641 | 1500 | 0.8913          | 0.7397   | 0.7255    | 0.7397 | 0.7178 |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.3